Placental extracellular vesicle trafficking in murine pregnancy
The placenta is a critical extrafetal disc-shaped organ responsible for the growth and development of the fetus during pregnancy. Anatomically, the placenta is at the interface of maternal and fetal tissues and provides a unique opportunity for cellular communication between the mother and fetus. Extracellular vesicles (EVs) are (40-150 nm) membrane-enclosed nanostructures that contain RNAs, proteins, and lipids that travel to different parts of the body and serve as a form of intercellular communication. During pregnancy, EVs are released in high quantities from the placenta and have been postulated to target multiple maternal cell types, including those of the vascular and immune systems. However, most studies on pregnancy-associated EVs have used clinical samples and in vitro models. To date, few studies have taken advantage of murine models in which pregnancy can be precisely timed and manipulated. The placenta secretes copious amounts of exosomes into maternal blood, but the localization of placental EVs in vivo and mechanisms mediate their trafficking remain understudied. Specifically, quantitative cellular measurements of placental EV localization and in vivo models of studying placental EVs are not well characterized. In this dissertation, I develop a computational software package tidyNano to process EV quantification data across murine gestation and characterize alterations in EV concentration during healthy pregnancy and during inflammation-associated preterm birth. Next, I demonstrate specific, preferential trafficking of placental EVs to interstitial macrophages in maternal lungs as well as Kupffer cells in the liver, with outer membrane integrins α3β1, α5β1, and αVβ3 mediating trafficking to these tissues. Finally, I establish a murine model for identifying fetal cells and placental EVs and propose a framework for studying maternal-fetal interactions in vivo during pregnancy. Collectively, the work described in this dissertation provides a computational framework to analyze nanoparticle data, identifies how placental EVs target specific maternal tissues, and provides a novel mouse model to study placental EV trafficking in vivo.
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- In Collections
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Electronic Theses & Dissertations
- Copyright Status
- Attribution 4.0 International
- Material Type
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Theses
- Authors
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Nguyen, Sean Lam-Vien
- Thesis Advisors
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Petroff, Margaret G.
- Committee Members
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Olson, Lawrence
Rockwell, Cheryl
Ralston, Amy
Fazleabas, Asgerally
Racicot, Karen
- Date Published
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2020
- Subjects
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Molecular biology
- Degree Level
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Doctoral
- Language
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English
- Pages
- 127 pages
- ISBN
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9798698570820
- Permalink
- https://doi.org/doi:10.25335/h2r9-q219